On Being A Data Skeptic

"Data is here, it's growing, and it's powerful." Author Cathy O'Neil argues that the right approach to data is skeptical, not cynical––it understands that, while powerful, data science tools often fail. Data is nuanced, and "a really excellent skeptic puts the term 'science' into 'data science.'" The big data revolution shouldn't be dismissed as hype, but current data science tools and models shouldn't be hailed as the end-all-be-all, either.

Understand the essentials of the Snowflake Database and the overall Snowflake Data Cloud. This book covers how Snowflake’s architecture is different from prior on-premises and cloud databases. The authors also discuss, from an insider perspective, how Snowflake grew so fast to become the largest software IPO of all time. Snowflake was the first database made specifically to be optimized with a cloud architecture. This book helps you get started using Snowflake by first understanding its architecture and what separates it from other database platforms you may have used. You will learn about setting up users and accounts, and then creating database objects. You will know how to load data into Snowflake and query and analyze that data, including unstructured data such as data in XML and JSON formats. You will also learn about Snowflake’s compute platform and the different data sharing options that are available. What You Will Learn Run analytics in the Snowflake Data Cloud Create users and roles in Snowflake Set up security in Snowflake Set up resource monitors in Snowflake Set up and optimize Snowflake Compute Load, unload, and query structured and unstructured data (JSON, XML) within Snowflake Use Snowflake Data Sharing to share data Set up a Snowflake Data Exchange Use the Snowflake Data Marketplace Who This Book Is For Database professionals or information technology professionals who want to move beyond traditional database technologies by learning Snowflake, a new and massively scalable cloud-based database solution

An all-encompassing guide to skeptical thinking from podcast host and academic neurologist at Yale University School of Medicine Steven Novella and his SGU co-hosts, which Richard Wiseman calls "the perfect primer for anyone who wants to separate fact from fiction." It is intimidating to realize that we live in a world overflowing with misinformation, bias, myths, deception, and flawed knowledge. There really are no ultimate authority figures-no one has the secret, and there is no place to look up the definitive answers to our questions (not even Google). Luckily, The Skeptic's Guide to the Universe is your map through this maze of modern life. Here Dr. Steven Novella-along with Bob Novella, Cara Santa Maria, Jay Novella, and Evan Bernstein-will explain the tenets of skeptical thinking and debunk some of the biggest scientific myths, fallacies, and conspiracy theories-from anti-vaccines to homeopathy, UFO sightings to N- rays. You'll learn the difference between science and pseudoscience, essential critical thinking skills, ways to discuss conspiracy theories with that crazy co- worker of yours, and how to combat sloppy reasoning, bad arguments, and superstitious thinking. So are you ready to join them on an epic scientific quest, one that has taken us from huddling in dark caves to setting foot on the moon? (Yes, we really did that.) DON'T PANIC! With The Skeptic's Guide to the Universe, we can do this together. "Thorough, informative, and enlightening, The Skeptic's Guide to the Universe inoculates you against the frailties and shortcomings of human cognition. If this book does not become required reading for us all, we may well see modern civilization unravel before our eyes." -- Neil deGrasse Tyson "In this age of real and fake information, your ability to reason, to think in scientifically skeptical fashion, is the most important skill you can have. Read The Skeptics' Guide Universe; get better at reasoning. And if this claim about the importance of reason is wrong, The Skeptics' Guide will help you figure that out, too." -- Bill Nye

A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data. “A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don’t feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data. You don’t need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit. We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.

Data science has never had more influence on the world. Large companies are now seeing the benefit of employing data scientists to interpret the vast amounts of data that now exists. However, the field is so new and is evolving so rapidly that the analysis produced can be haphazard at best. The 9 Pitfalls of Data Science shows us real-world examples of what can go wrong. Written to be an entertaining read, this invaluable guide investigates the all too common mistakes of data scientists - who can be plagued by lazy thinking, whims, hunches, and prejudices - and indicates how they have been at the root of many disasters, including the Great Recession. Gary Smith and Jay Cordes emphasise how scientific rigor and critical thinking skills are indispensable in this age of Big Data, as machines often find meaningless patterns that can lead to dangerous false conclusions. The 9 Pitfalls of Data Science is loaded with entertaining tales of both successful and misguided approaches to interpreting data, both grand successes and epic failures. These cautionary tales will not only help data scientists be more effective, but also help the public distinguish between good and bad data science.

THE NEW YORK TIMES BESTSELLER FROM THE AUTHOR OF 10% HAPPIER Too busy to meditate? Can’t turn off your brain? Curious about mindfulness but more comfortable in the gym? This book is for you. You’ll also get access to guided audio meditations on the 10% Happier app, to jumpstart your practice from day one. ABC News anchor Dan Harris used to think that meditation was for people who collect crystals, play Ultimate Frisbee, and use the word “namaste” without irony. After he had a panic attack on live television, he went on a strange and circuitous journey that ultimately led him to become one of meditation’s most vocal public proponents. Harris found that meditation made him more focused and less yanked around by his emotions. According to his wife, it also made him less annoying. Science suggests that the practice can lower your blood pressure, mitigate depression and anxiety, and literally rewire key parts of the brain. So what’s holding you back? In Meditation for Fidgety Skeptics, Harris and Jeff Warren, a masterful teacher and “Meditation MacGyver,” embark on a gonzo cross-country quest to tackle the myths, misconceptions, and self-deceptions that keep people from meditating. It is filled with game-changing and deeply practical meditation instructions—all of which are also available (for free) on the 10% Happier app. This book is a trip worth taking. Praise for Meditation for Fidgety Skeptics “If you’re intrigued by meditation but don’t know how to begin—or you’ve benefited from meditation in the past but need help to get started again—Dan Harris has written the book for you. Well researched, practical, and crammed with expert advice, it’s also an irreverent, hilarious page-turner.”—Gretchen Rubin, author of The Happiness Project “The ABC News anchor, a ‘defender of worrying’ who once had an anxiety attack on air, offers a hilarious and stirring account of his two-steps-forward-one-step-back campaign to sort ‘useless rumination’ from ‘constructive anguish’ via mindfulness, along with invaluable suggestions for following in his footsteps.”—O: The Oprah Magazine

Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.